# datasets
emissions = read_csv("https://raw.githubusercontent.com/mrbarron3/group_project/main/data.csv")
emissions = emissions %>%
group_by(Country) %>%
mutate(avg_epsv = mean(Environmental_Policy_Stringency_Value)) %>%
ungroup() %>%
mutate(total_avg_epsv = median(avg_epsv)) %>%
arrange(desc(avg_epsv), Year)
emissions_top = emissions %>%
filter(avg_epsv > total_avg_epsv)
emissions_bottom = emissions %>%
filter(avg_epsv <= total_avg_epsv)
emissions_groups = emissions %>%
group_by(Country) %>%
count()
emissions_diff = emissions %>%
group_by(Country) %>%
mutate(year_max = max(Year), year_min = min(Year)) %>%
filter((Year == year_max | Year == year_min) & (Year == 2020 | Year == 1990)) %>%
mutate(Year = as.character(Year)) %>%
select(Country, Year, Environmental_Policy_Stringency_Value) %>%
pivot_wider(names_from = Year, values_from = Environmental_Policy_Stringency_Value) %>%
mutate(diff = `2020` - `1990`) %>%
drop_na()
emi_90_20 = emissions_diff %>%
pivot_longer(c("2020", "1990"), names_to = "Year", values_to = "epsi")
emi_90_20
## # A tibble: 54 × 4
## # Groups: Country [27]
## Country diff Year epsi
## <chr> <dbl> <chr> <dbl>
## 1 Switzerland 3 2020 4.5
## 2 Switzerland 3 1990 1.5
## 3 Japan 2.19 2020 3.78
## 4 Japan 2.19 1990 1.58
## 5 Finland 2.53 2020 4.11
## 6 Finland 2.53 1990 1.58
## 7 France 3.44 2020 4.89
## 8 France 3.44 1990 1.44
## 9 Denmark 3.31 2020 3.72
## 10 Denmark 3.31 1990 0.417
## # … with 44 more rows
emissions_diff
## # A tibble: 27 × 4
## # Groups: Country [27]
## Country `1990` `2020` diff
## <chr> <dbl> <dbl> <dbl>
## 1 Switzerland 1.5 4.5 3
## 2 Japan 1.58 3.78 2.19
## 3 Finland 1.58 4.11 2.53
## 4 France 1.44 4.89 3.44
## 5 Denmark 0.417 3.72 3.31
## 6 Sweden 0.694 3.83 3.14
## 7 Italy 1.61 3.72 2.11
## 8 Norway 0.472 3.94 3.47
## 9 Germany 1.44 3.47 2.03
## 10 Netherlands 1.56 3.47 1.92
## # … with 17 more rows
nrow(emissions_groups)
## [1] 33
# line plot
line_plot = ggplot(emissions, aes(x = Year, y = Environmental_Policy_Stringency_Value, color = Country)) +
geom_line() +
geom_point(size = 0.5) +
labs(y = "Environment Policy Stringency Value", title = "Environmental Policy Stringency Indicies Over the Years")
ggplotly(line_plot)
# probably too much info
# density ridges
ggplot(emissions) +
geom_density_ridges(aes(Environmental_Policy_Stringency_Value, reorder(Country, Environmental_Policy_Stringency_Value)))# +
# labs(y = "Country", title = "Environmental Policy Stringency Indicies By Country", subtitle = "Over the Years 1990-2020 where available")
# combined box plots
a = ggplot(emissions_top) +
geom_boxplot(aes(Environmental_Policy_Stringency_Value, reorder(Country, Environmental_Policy_Stringency_Value, mean))) +
labs(y = "Country", title = "a")
b = ggplot(emissions_bottom) +
geom_boxplot(aes(Environmental_Policy_Stringency_Value, reorder(Country, Environmental_Policy_Stringency_Value, mean))) +
labs(y = "Country", title = "b")
a + b +
plot_annotation(title = "Environmental Policy Stringency Indicies By Country", subtitle = "1990-2020")
# single boxplot
ggplot(emissions) +
geom_boxplot(aes(Environmental_Policy_Stringency_Value, reorder(Country, Environmental_Policy_Stringency_Value, mean))) +
labs(x = "Environmental Policy Stringency Index Value", y = "Country", title = "Environmental Policy Stringency Indicies By Country, 1990-2020", subtitle = "A Smaller Subset of Years May be Used Depending on Data Availability")
# bar plot with differences between newest and oldest data
ggplot(emissions_diff) +
geom_col(aes(x = reorder(Country, diff), y = diff)) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
labs(x = "Country", y = "Increase Amount", title = "Increase Between 1990 and 2020 Environment Policy Stringency Index Value", subtitle = "Only Includes Countries Where Both 2020 and 1990 Data is Available") +
scale_y_continuous(expand = c(0, 0))
# double bar plot
ggplot(emi_90_20) +
geom_col(aes(x = reorder(Country, epsi, max), y = epsi, fill = Year), width = 0.7, position = "dodge") +
scale_fill_manual(values = c("#a67abf", "#99bf7a")) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
scale_y_continuous(expand = c(0, 0)) +
labs(x = "Country", y = "Environmental Policy Stringency Index", title = "Environmental Policy Stringency Index by Country and Year", subtitle = "Only Includes Countries Where Both 2020 and 1990 Data is Available")
